Discrete Cosine Transform (DCT) coding, as used for image compression, is a lossy compression technique. The DCT compression technique involves generating DCT coefficients for each image block, quantizing the DCT coefficients, and then encoding the quantized coefficients using variable length encoding.
Artifacts are introduced into the recovered image when using DCT coding. Block artifacts are introduced because the image is decomposed into blocks in order to perform the DCT processing. Ringing artifacts are caused as a result of the Gibbs phenomenon, which results from truncation of high frequency coefficients. Post filtering of the decoded video stream is thus an essential step to remove these artifacts. Block artifacts are present in smooth areas and ringing artifacts are most visible around strong edges.
The most important aspect of post processing is to reduce blocking and ringing artifacts without causing image degradation. Current approaches use complex detection processes for detecting block boundaries. Many techniques also use complex processes in order to avoid edges when processing to remove ringing artifacts. In addition they use temporal filtering, motion vectors and motion compensation. Furthermore, many current methods depend on a priori knowledge about the DCT block processing used for encoding. As a result, conventional systems are inflexible and computationally expensive.